A t test is a statistical tool mostly used in Hypothesis testing. It is used to determine whether the differences of means between two groups are likely due to a real effect or just by a random chance. This test is used when you want to compare the means of two groups or samples and determine the difference between them is statistically significant. There are different types of T test, the most commonly used techniques are Independent Samples and Paired Samples. In independent sample test we compare the averages of two independent groups and assess if there significant difference between, which determines whether the difference between them is due to real effect or by a random chance. In paired sample test we compare the averages of two related groups.
Steps in T – Test
The basic steps to perform t-test are , the first step of this process is to formulate the hypothesis ( Null Hypothesis and Alternative Hypothesis) , if suppose we are comparing means of two different samples then we must formulate for Null and Alternative Hypothesis. The next step is collecting data from two samples and then the collected data is used to calculate the t-statistic using means of two samples, standard deviation of two samples , and the size of the samples. The next step is to calculate the p value, this p value helps us to determine whether the results occurred are likely or unlikely to be happened by a random chance. If the p value is small typically < 0.05 then , it shows that results occurred are unlikely to be happened by a random chance. If the p value is large typically greater > 0.05 then , it shows that the results occurred are very likely to be happened by a random chance.